Mapping the denominator: Spatial demography in the measurement of progress

International Health

Volumn 6, Issue 3, 2014, Pages 153-155

  Tatem, Andrew J ^a,b,c  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^b NATIONAL INSTITUTES OF HEALTH   (United States)

^c FLOWMINDER FOUNDATION   (Sweden)

Author keywords

Burden estimation; Census; Demography; Health metrics; Mapping; Population

Indexed keywords

ANGOLA; ARTICLE; GEOGRAPHIC MAPPING; HUMAN; INDIA; MADAGASCAR; NIGERIA; PAKISTAN; POPULATION DISTRIBUTION; POPULATION SIZE; PREVALENCE; PUBLIC HEALTH; SATELLITE IMAGERY; SIERRA LEONE; URBANIZATION; VULNERABLE POPULATION; DEMOGRAPHY; HEALTH SURVEY; POPULATION AND POPULATION RELATED PHENOMENA; POPULATION DENSITY; PROCEDURES; SPATIAL ANALYSIS;

DEMOGRAPHY; EPIDEMIOLOGIC MEASUREMENTS; HUMANS; POPULATION DENSITY; POPULATION SURVEILLANCE; SPATIAL ANALYSIS;

EID: 84907550448     PISSN: 18763413     EISSN: 18763405     Source Type: Journal    
DOI: 10.1093/inthealth/ihu057     Document Type: Article

References (18)

1. WHO.World Malaria Report 2014. Geneva:World Health Organization; 2014.
2. Gething PW, Patil AP, Smith DL et al. . A new world malaria map: Plasmodium falciparum endemicity in 2010. Malar J 2011;10:378.
3. Bhatt S, Gething PW, Brady OJ et al. . The global distribution and burden of dengue. Nature 2013;496:504-7.
4. Garske T, Van Kerkhove MD, Yactayo S et al. . Yellow Fever in Africa: estimating the burden of disease and impact of mass vaccination from outbreak and serological data. PLoS Med 2014;11:e1001638.
5. Cairns M, Roca-Feltrer A, Garske T et al. . Estimating the potential public health impact of seasonal malaria chemoprevention in African children. Nat Commun 2012;3:881.
6. Griffin JT, Ferguson NM, Ghani AC. Estimates of the changing age-burden of Plasmodium falciparum malaria disease in sub-Saharan Africa. Nat Comms 2014;5:3136.
7. Patil AP, Gething PW, Piel FB, Hay SI. Bayesian geostatistics in health cartography: the perspective of malaria. Trends Parasitol 2011;27:246-53.
8. United Nations Population Division. World population prospects, 2012 revision. Geneva: United Nations; 2012.
9. Central Intelligence Agency. The World Factbook. Washington D.C., USA: US Government Printing Office; 2014.
10. Tatem AJ, Campiz N, Gething PW et al. . The effects of spatial population dataset choice on estimates of population at risk of disease. Popul Health Metr 2011;9:4.
11. Tatem AJ, Garcia AJ, Snow RW et al. . Millennium development health metrics: where do Africa's children and women of childbearing age live? Popul Health Metr 2013;11:11.
12. Esch T, Taubenböck H, Felbier A et al. . The path to mapping the global urban footprint using TanDEM-X data. Proc ISPRS 2011:34.
13. Pesaresi M, Ehrlich D, Caravaggi I et al. . Toward global automatic built-up area recognition using optical VHR imagery. IEEE App Earth Obs Rem Sens 2011;4:923-34.
14. Bengtsson L, Lu X, Thorson A et al. . Improved response to disasters and outbreaks by tracking population movements with mobile phone network data: a post-earthquake geospatial study in Haiti. PLoS Med 2011;8:e1001083.
15. Gething PW, Kirui VC, Alegana VA et al. . Estimating the number of paediatric fevers associated with malaria infection presenting to Africa's public health sector in 2007. PLoS Med 2010;7: e1000301.
16. Murray CJ, Rosenfeld LC, Lim SS et al. . Globalmalaria mortality between 1980 and 2010: a systematic analysis. Lancet 2012;379:413-31.
17. Schur N, Vounatsou P, Utzinger J. Determining treatment needs at different spatial scales using geostatistical model-based risk estimates of schistosomiasis. PLoS Negl Trop Dis 2012;6:e1773.
18. Sankoh O, Byass P. The INDEPTH Network: filling vital gaps in global epidemiology. Int J Epidemiol 2012;41:579-88.